World Journal of Oncology, ISSN 1920-4531 print, 1920-454X online, Open Access
Article copyright, the authors; Journal compilation copyright, World J Oncol and Elmer Press Inc
Journal website https://wjon.elmerpub.com

Original Article

Volume 16, Number 1, February 2025, pages 30-50

Expression Profile of Thymidine Kinase Genes in Cervical Squamous Cell Carcinoma Confirmed by Various Detection Methods

Figures

Figure 1.
Figure 1. The overall design of the current study.
Figure 2.
Figure 2. PRISMA flow diagram for the current study.
Figure 3.
Figure 3. TK1 expression in CESC from external microarrays and RNA-seq datasets. Violin plots for: (a) GPL570; (b) GPL571; (c) GPL6244; (d) GPL96; (e) GPL4133; (f) GPL1053 and GPL1052; (g) GPL201; (h) GPL3515; (i) GPL4926; (j) GPL7025; (k) GPL16238; (l) GPL1708; (m) TCGA-GTEx. N: non-cancer controls; T: CESC samples.
Figure 4.
Figure 4. The discriminatory ability of TK1 expression in distinguishing CESC from non-cancer tissues in each microarray and RNA-seq dataset. ROC curves for GPL570 (a), GPL571 (b), GPL6244 (c), GPL96 (d), GPL4133 (e), GPL1053 and GPL1052 (f), GPL201 (g), GPL3515 (h), GPL4926 (i), GPL7025 (j) GPL16238 (k), GPL1708 (l) and TCGA-GTEx datasets (m). AUC: area under curve.
Figure 5.
Figure 5. TK2 expression in CESC from external microarrays and RNA-seq datasets; N: non-cancer controls; T: CESC samples.
Figure 6.
Figure 6. The discriminatory ability of TK2 expression in distinguishing CESC from non-cancer tissues in each microarray and RNA-seq dataset. AUC: area under curve.
Figure 7.
Figure 7. Pooled TK1 expression in CESC tissues. (a) SMD forest. (b) sROC curve. SMD: standardized mean difference; sROC: summarized receiver’s operating characteristics.
Figure 8.
Figure 8. Pooled TK2 expression in CESC tissues. (a) SMD forest. (b) sROC curve. SMD: standardized mean difference; sROC: summarized receiver’s operating characteristics.
Figure 9.
Figure 9. TK1 protein levels in CESC from tissue microarrays. (a) Negative staining of TK1 in non-cancer squamous epithelium tissues (× 100). (b) Negative staining of TK1 in non-cancer squamous epithelium tissues (× 200); (c) Negative staining of TK1 in non-cancer squamous epithelium tissues (× 400); (d, g) Strong staining of TK1 in CESC tissues (× 100); (e, h) Strong staining of TK1 in CESC tissues (× 200); (f, i) Strong staining of TK1 in CESC tissues (× 400); (j) Violin plots of TK1 expression in CESC and non-cancer controls; (k) ROC curves of the discriminating ability of TK1 overexpression. N: non-cancer samples; T: CESC samples; AUC: area under curve.
Figure 10.
Figure 10. Perturbation effect of knocking down TK1 expression in various CESC cell lines. A lower Chronos score indicates a higher likelihood that the gene of interest is essential in a given cell line.
Figure 11.
Figure 11. The prognostic significance of TK1 and TK2 expression for CESC. (a) Kaplan-Meier survival curves for overall survival of CESC patients with low or high TK1 expression. (b) Kaplan-Meier survival curves for disease-free survival of CESC patients with low or high TK1 expression. (c) Kaplan-Meier survival curves for overall survival of CESC patients with low or high TK2 expression. (d) Kaplan-Meier survival curves for disease-free survival of CESC patients with low or high TK2 expression. HR: hazard ratio.
Figure 12.
Figure 12. The relationship between TK2 expression and the clinical progression of CESC. (a) TK2 expression in CESC patients with different cancer stages. (b) TK2 expression in CESC patients with different tumor histology. (c) TK2 expression in CESC patients with different status of nodal metastasis.
Figure 13.
Figure 13. The TK1 and TK2 gene alterations in CESC patients. (a) The mutation type of TK1 and TK2 in CESC patients. (b) The expression of TK1 and TK2 showed a negative correlation.
Figure 14.
Figure 14. The correlations between TK1 expression and the infiltration level of immune cells in CESC. Scatter plot of the correlations between TK1 expression and immune infiltration. TPM: transcripts per kilobase million.
Figure 15.
Figure 15. The correlations between TK2 expression and the infiltration level of immune cells in CESC. Scatter plot of the correlations between TK2 expression and immune infiltration. TPM: transcripts per kilobase million.
Figure 16.
Figure 16. The molecular docking model of targeted protein and vorinostat (a: TK1 protein; b: TK2 protein).

Tables

Table 1. Basic Information From All Included RNA-seq and Microarray Datasets of Cervical Cancer
 
DatasetPlatformCountryFirst authorSample typeNumber of tumor samplesNumber of non-cancer samples
GSE7803GPL96USARork KuickTissue6641
GSE9750GPL96USAMurty VundavalliTissue and cell lines
GSE46857GPL7025IndiaRita MulherkarTissue254
GSE14404GPL6699IndiaRajkumar TTissue2812
GSE29570GPL6244MexicoMariano Guardado-EstradaTissue18860
GSE52903GPL6244MexicoIngrid Medina MartinezTissue
GSE52904GPL6244MexicoIngrid Medina MartinezTissue
GSE89657GPL6244MexicoMauricio Salcedo VargasTissue and cell lines
GSE39001GPL6244MexicoAna Maria EspinosaTissue
GSE27678GPL571United KingdomIan RobertsTissue and cell lines3717
GSE63678GPL571USAProkopios Alexandros PolyzosTissue
GSE6791GPL570USAPaul AhlquistTissue100130
GSE27678GPL570United KingdomIan RobertsTissue and cell lines
GSE63514GPL570USAJohan den BoonTissue
GSE4482GPL4926IndiaChandan KumarTissue34
GSE138080GPL4133NetherlandsRenske DM SteenbergenTissue1010
GSE4482GPL3515IndiaChandan KumarTissue134
GSE39001GPL201MexicoAna Maria EspinosaTissue4312
GSE7410GPL1708NetherlandsPetra BiewengaTissue405
GSE55940GPL16238ChinaChen YeTissue55
GSE67522GPL10558United KingdomSweta Sharma SahaTissue2022
GSE26342GPL1053/GPL1052USANatalia ShulzhenkoTissue3420
TCGA-GTEx---Tissue30614

 

Table 2. Top 10 Drugs With the Smallest Fold Changes Targeting TK1
 
Drug namePqFold changeSpecificity
Amsacrine1.93729 × 10-223.71892 × 10-20-3.145120.000296033
Teniposide1.81285 × 10-172.69123 × 10-15-2.923980.000296824
Tanespimycin2.29969 × 10-221.00411 × 10-19-2.89090.000137912
MG-1323.37601 × 10-145.36979 × 10-11-2.821850.000456621
BRD-K685489589.27931 × 10-321.57734 × 10-29-2.81780.000294118
SA-19197101.37796 × 10-133.83556 × 10-10-2.806770.001135074
Torin-21.39394 × 10-176.33474 × 10-15-2.806570.000264831
Vorinostat6.60819 × 10-173.75385 × 10-15-2.78220.000131492
PP-1103.48166 × 10-294.78578 × 10-27-2.778530.000152602

 

Table 3. Top 10 Drugs With the Smallest Fold Changes Targeting TK2
 
Drug namePqFold changeSpecificity
Trichostatin-a8.01858 × 10-111.16704 × 10-82.233090.000340136
Trichostatin-a7.35718 × 10-142.08435 × 10-121.653480.000168492
BRD-K827508141.72195 × 10-60.0001062171.627140.000577701
Trichostatin-a2.55848 × 10-69.05758 × 10-51.576370.000383877
Trichostatin-a2.433 × 10-117.10065 × 10-101.471620.000194477
Panobinostat3.75935 × 10-221.38141 × 10-201.461210.000128074
Apicidin4.55567 × 10-191.0074 × 10-171.432910.000134174
Trichostatin-a9.1091 × 10-111.3011 × 10-91.43190.000171028
Tozasertib5.76929 × 10-60.0000521391.411040.000120802
Vorinostat1.72852 × 10-102.62555 × 10-91.382050.00017328